Logic of the Influence of Non-Monetary Information Signals of the Usa on the Excess Return of Ukrainian Stock Market

The main task for the Central Bank is ensuring the stability of the national currency. For this purpose, it tends to use traditional monetary regulation instruments. There are interest rates regulation, currencies intervention, administrative restriction, money supply adjustment and so on. A significant number of these traditional tools are effective. However, it is very difficult to assess the effectiveness of the regulators influence. Therefore, the purpose of the work is to define the theoretical substantiation of the basic monetary regulation instruments effectiveness and estimate its influence on the economy growth indicators in Ukraine. This article is based on the theoretical principles and methods of macroeconomic analysis; the system approach methods to define the main monetary regulation instruments of finance system and economy. The study presents a regression models with paired and multiple variables. For these models R-Studio instruments are the main tools of quality estimation and results interpretation. The article shows the results of statistical analysis of national currency rate and consumer price index which is based on open data of Ukraine economy trends for the period from 2007 till 2019. Traditionally econometric methods are used to find out long run relationships between basic economy indicators (agriculture and industry outputs, average salary, stock index growth etc.) and both monetary information and regulation instruments. Authors develop the regressive models of influence of Central Bank regulation instruments of monetary and economic stability. The paper presents conclusions regarding trends and problems in the implementation of Ukraine's monetary policy, it's influences on the currency stability and economic growth trends. Implementation of the proposed measures will increase monetary policy effectiveness and define the directions of the further research in forecasting inflationary and course-forming factors of the development of the national economy and financial system of Ukraine. The key focus of further research is to define an adequate indicator that determines the real level of inflation, which must evaluate a whole range of factors reducing the real value of money.

Econometric Models of Monetary Policy Effectiveness in Ukraine

Baranovskyi¹,

Kuzheliev²,

Zherlitsyn³

et al. 2019

Evaluation of Ukrainian Banks’ Business Models by the Structural and Functional Groups Analysis Method

Zarutska¹,

Novikova²,

Pavlov³

et al. 2022

A method of identifying banks’ business models and studying the features of their risk profile, considering the system of indicators featuring the structure of assets, liabilities, income, expenses, and other qualitative indicators based on monthly statistical reporting. Kohonen's self-organizing maps (SOM) are used to process large data sets, revealing objects’ hidden features by forming homogeneous groups according to similar values of a large system of indicators. The choice of the system of indicators that play the most significant role in describing the business models of modern banks is substantiated. The proposed method makes it possible to group banks with homogeneous characteristics into so-called structural-functional groups and studies the change in the characteristics of groups of banks over time to compare their behavior during periods of active development of the system and during a crisis. That approach is useful for studying the banking system at the macro level, as it provides a quantitative measure of its financial stability. The more banks are in groups with negative values of parameters, increased risks, and unprofitable performance, the worse the general state of the system. The method also allows studying the features of each structural and functional group and the business models’ features at the meso-level. The number and composition of banks inherent in any group change dynamically, which characterizes the features of the relevant business model in a particular period. The averages of each group reflect the objective changes in the banking system structure. In addition, the SOM trajectory can be built for each individual bank determining the development of its strategy, features of a particular business model, and risk profile. At the micro-level, it allows comparing the features of individual banks within the SFGB and models ways to improve efficiency and financial stability by forecast values for SOM. An extensive system of indicators used to form structural and functional groups of banks allows to quickly respond to changes in the banking system, identify areas of increased risk and explore the adequacy and effectiveness of banks’ business models.

Changes in Ukrainian Banks ‘Business Models in Times of Military Crisis

Zarutska¹,

Ponomarоva²,

Pavlov³

et al. 2022

The article analyzes changes in the business models of Ukrainian banks using the author's method of structural and functional groups of banks (SFGB). The method’s basis is the processing, systematization, and visualization of the system’s values of banks’ financial indicators using Kohonen’s self-organizing map (SOM). Depending on the level distribution of a large number of indicators that characterize the structure of assets, liabilities, income, expenses, and other qualitative indicators that describe the business models of each bank on successive reporting dates, homogeneous groups of banks are formed. The purpose of this study is to compare the key features of the banking system as of January 1 and September 1, 2022, and the corresponding changes in business models.Over the eight months of 2022, the number of banks with corporate lending increased slightly, but the resource base of these banks gradually changed. The number of banks with retail financing decreased at the expense of banks with current resources. During an increase in the discount rate and in the price of refinancing loans, banks’ business model that attracts resources on the interbank market and places them in securities has shrunk. At the same time, the number of banks with an increased level of securities in assets and corporate financing increased. The quality of the portfolio indicates the increased credit risks of the respective large state banks.The drawback of the proposed method is the dependence of conclusions on official banks 'statements that do not always reflect nuisances of financial position. Within small banks, we can sometimes observe that current changes in clients' account balances affect the position in SFGB. The SFGB method can be applied to analyze trends and estimate the probability of subsequent structural changes. For each bank, one can observe the trajectory change on the map and investigate the reasons for the change in business strategy.